One potential approach for learning in the frequency domain might simply be to convert sensing signals into the frequency domain first, and then apply conventional neural network components, possibly extending them to support operations on complex-numbers so they can represent frequency-domain quantities [1]}. These approaches miss two key opportunities for improvement, described below, that we take advantage of in this work. As a result, our work leads to more accurate results, as shown in the evaluation section. The two reasons that account for our improvements are as follows.
